Preadmission academic achievement criteria as predictors of nursing program completion and NCLEX -RN success
2009
- 226Usage
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage226
- Downloads160
- Abstract Views66
Thesis / Dissertation Description
Admission policies and practices in higher education, including those in nursing programs, are diverse; yet administrators have traditionally relied upon preadmission academic achievement for selection of qualified students. Higher education administrators have the responsibility to serve the institution and all of its constituents, ensuring that admission policies and regular systematic evaluation of those policies are important aspects of that service.;The nursing shortage and limited resources have pressed nursing schools to implement innovative strategies to increase the number of qualified graduates. State University's School of Nursing has used a score sheet to rank associate degree nursing applicants since 1984. The preadmission score sheet includes cumulative GPA, standardized test scores, prerequisite and support course grades, and LPN (licensed practical nurse) licensure. Students cannot become registered nurses unless they complete the nursing program and pass the National Council Licensure Examination for Registered Nurses (NCLEX-RN).;The purpose of this study was to determine the ability of various preadmission academic achievement-related variables to predict nursing program completion and NCLEX-RN success. The sample consisted of 294 students admitted to the State University associate degree nursing program in the Fall of 2005, 2006, and 2007. Logistic regression models were used to determine which preadmission academic achievement variables were most predictive of program completion and NCLEX-RN success.;TEAS science scores were predictive of both program completion and NCLEX-RN success. TEAS reading scores were predictive of NCLEX-RN success but not program completion. Science GPA was predictive of program completion, and health-related coursework GPA was predictive of NCLEX-RN success. Demographic factors were also evaluated for the ability to predict success, and of those variables, student type (traditional versus nontraditional) was predictive of both outcome variables. Nontraditional students were most likely to succeed.;Specific recommendations were presented for policy and future research. This study suggested greater emphasis on variables predictive of student success in admission policy, caution when using test scores without context for admission decisions, and variety when selecting those measures used to rank applicants. This study also suggested that the largest amount of variance in student success is yet to be explained and presented recommendations for study replication and expansion.
Bibliographic Details
West Virginia University Libraries
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know